Database community has made significant research efforts to
optimize query processing on GPUs in the past few years.
However,
we can hardly find that GPUs have been truly adopted in major data warehousing production systems.
To understand main reasons behind this fact,
we have conducted a comprehensive study to evaluate the performance of processing complex data warehousing queries
by varying query characteristics, software optimization techniques, and GPU hardware configurations.
Our study focuses on 
the two fundamental components of query execution on GPUs,
PCIe data transfer and kernel execution,
aiming at gaining deep insights on 
how they are affected by various factors from software to hardware.
Furthermore, 
we also propose an analytical model to understand and predict the variations of the two factors.
Based on our study, we present our performance insights and prediction
for warehousing query execution on GPUs.


